ArticleNursing research
Evaluating Feasibility of Personal Diabetes Device Data Collection for Research.
Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Simulation Platform Development for Diabetes and Technology Self-Management.Journal of diabetes science and technology · 2022Article
- Expect the unexpected: Adolescent and pre-teens' experience of diabetes technology self-management.Pediatric diabetes · 2021Article
- Use of continuous glucose monitoring in obesity research: A scoping review.Obesity research & clinical practiceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDiabetes devices, like insulin pumps and continuous glucose monitors (CGMs), capture and store patient adherence and utilization data that can be retrieved or downloaded providing objective information on self-management behaviors; yet, diabetes device data remain underutilized in research.
objectiveThe aim of the study was to examine the usability and feasibility of personal diabetes device data collected using a clinical download platform retooled for research purposes.
methodsInvestigators evaluated the feasibility of raw diabetes device data collection. One hundred eight preteens and adolescents with Type 1 diabetes and their parents provided consent/assent.
resultsData were successfully collected from the diabetes devices (insulin pumps and CGM) of 97 youth using a clinical download software adapted for research, including data from all three commercially available CGM systems and insulin pumps brands, which contained all current and previous models of each insulin pump brand. The time required to download, mode of connection, and process varied significantly between brands. Despite the use of an agnostic download software, some outdated device brands and cloud-based CGM data were unsupported during data collection. Within the download software, dummy clinical accounts were created for each study participant, which were then linked back to a master study account for data retrieval. Raw device data were extracted into seven to eight Excel files per participant, which were then used to develop aggregate daily measures. DISCUSSION: Our analysis is the first of its kind to examine the feasibility of raw diabetes device data using a clinical download software. The investigators highlight issues encountered throughout the research process, along with mitigating strategies to inform future inquiry.
conclusionThis study demonstrates the feasibility of raw data collection, from a wide variety of insulin pump and CGM brands, through the retooling of a clinical download software. Data from these personal devices provide a unique opportunity to study self-management behavior and the glycemic response of individuals in their everyday environments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.